
AWS CodePipeline Experts in Germany
, matched in minutes by AIHire experts who design CI/CD workflows, connect AWS CodeBuild with deployment services, and automate releases across cloud environments. FRATCH matches you quickly and precisely with vetted, available freelancers who fit your AWS CodePipeline project.
Meet FRATCH Experts in Germany, who have recently used AWS CodePipeline
Hassan A.
Last position:
DevOps & Observability Consultant at ALDI South (Albrecht's Discount)
- Supporting the DevOps team in Terraform-managed, multi-region AWS infrastructure to achieve environment parity.
- Developed end-to-end CI/CD pipelines using AWS CodePipeline, CodeBuild, and CodeDeploy, automating the build and deployment.
- Maintained pre- and post-deployment scripts to automate critical tasks such as database schema migrations and environment sanity checks.
- Implemented CI/CD flow specifically for hotfixes via separate Git branches, managing back-merge activities from feature branches to release branches to ensure code integrity through automated conflict resolution.
- Deployed a dedicated, lightweight sanity check application hosted cost-effectively on Azure Container Apps to run automated health and basic functional checks as a post-deployment activity triggered via pipeline.
- Investigated production incidents through code changes and AWS CloudWatch logs.
- Coordinated integration of Dynatrace APM and its APIs for monitoring purposes.
- Full stack QA strategist for a high-traffic e-commerce platform built on a layered architecture for the back-end testing of core platform services, especially the order management system in Zed and Glue layers.
- Managed automation activities, testing process, and refactoring practices.
- Responsible for framework migrations, setup, and training for new automation frameworks.
- Promoted a shift-left approach within the QA team and created the test concept.
- Participated in meetings with IT managers, business owners, product owners, and team members.
- Designed and implemented contract testing to validate API schema compatibility between the order management system and the Zed and Glue layers, reducing production-relevant breaking changes by approximately 3%.
- Led the migration to a multi-environment framework that enabled test execution across 4 country configurations from a single codebase.
- Integrated automated unit and functional tests directly into the GitLab CI/CD pipeline, reducing pipeline runtime by 32%.
- Coached and trained 5 QA engineers across Germany and Hungary in test automation, framework architecture, and best practices.
- Architected a layered backend test automation framework separating business logic, API request builders, and the database layer.
- Piloted AI-assisted testing with Playwright Agents, the Playwright MCP Server, and GitHub Copilot for automated test generation, execution, and self-healing Playwright scripts.
Jorge P.
Last position:
Software Engineer – AWS and Kubernetes Specialist at Citti
- Creation, maintenance and hardening of Kubernetes clusters employing Ansible and ArgoCD
- Keywords: Ansible, AWX, Kubernetes, NetApp, Prometheus, CI/CD ArgoCD, SSO, Fluent-bit, HAProxy, Calico, Keycloak, oauth2-proxy, SealedSecrets, kubeseal, Aqua kube-bench, CIS-Benchmarks, Aqua Trivy operator
Artyom N.
Last position:
AI Automation Engineer & Solution Architect at Technology Research Project
Designed and developed an AI-powered automation platform using n8n to analyze social media niches, identify target audiences, and automate marketing strategy generation. The solution combined AI agents, workflow orchestration, and data analysis to automate research processes and generate data-driven insights.
- Designed and implemented complex automation workflows using n8n
- Developed AI-powered analysis agents for market and audience research
- Integrated multiple APIs and AI services into automated workflows
- Built automated market, competitor, and target audience analysis pipelines
- Leveraged Large Language Models (LLMs) for information summarization, classification, and prioritization
- Containerized and deployed the platform using Docker
Technologies: n8n, AI Agents, OpenAI APIs, Prompt Engineering, LLMs, Docker, Linux, REST APIs, Webhooks
Alexander Z.
Last position:
Fullstack Developer and DevOps Engineer at Freelancer
- Developing the infrastructure and improving existing infrastructure: Jenkins, Gitlab Pipeline, OpenShift, Docker, Helm Chart, Kubernetes, Artifactory, CodePipeline, CodeArtifact, Python
- Documenting solutions in Jira/Confluence
- Supporting other colleagues in different technical areas
Thorsten B.
Last position:
Senior Backend Engineer at VTG Rail Europe
traigo is VTG's digital rail logistics and fleet management platform. It processes large volumes of telemetry, mileage, geofence, sensor and wagon-movement events in near real time and provides operational services for rail logistics customers across Europe.
As part of Team Customer Selfcare, I worked on the design, implementation, optimisation and operation of large-scale backend services and event-driven processing pipelines — covering both feature development and operational ownership of business-critical production systems. I also regularly acted as first responder for production incidents, data inconsistencies and performance investigations across multiple distributed services.
- Design and implementation of event-driven backend services.
- Migration and replacement of legacy processing pipelines.
- Development of replay / rebuild mechanisms for large event datasets.
- High-throughput asynchronous event processing on SNS / SQS.
- Database and query optimisation for PostgreSQL and DynamoDB.
- Design of scalable read / write models and aggregation pipelines.
- Production troubleshooting and operational support.
- Performance tuning and infrastructure scaling.
- Design and stabilisation of integration and system tests.
- Technical concepts, architecture documentation, and cross-team collaboration.
- Support the further development of existing GitLab CI/CD pipelines
Geofence & Wagon Stay Processing
- Algorithm to detect vehicles within geofences (entry, exit, dwell time).
- Event sourcing with guaranteed chronological order within the affected time window.
- Refactored geofence event and wagon-stay processing logic for performance.
- Resolved race conditions and event-ordering problems in distributed services; server-side filtering, aggregation and optimised query pipelines.
- Repair and replay tooling for corrupted or inconsistent movement data.
Fleet Metadata & Mileage
- Modernised the service; migrated storage from DynamoDB to PostgreSQL to improve traceability and accelerate new features.
- Scalable mileage aggregation and replay mechanisms.
- Read / write models and optimised queries for high-volume mileage calculations.
Sensor & Telematics Integration
- Integrated telemetry and sensor processing pipelines.
- Snapshot and state-calculation logic for sensor systems.
- APIs and persistence models for wagon sensor data; data-quality improvements.
- Further development of a service using gRPC for intra-service communication.
Movement Segment Processing & Routing
- Migrated services to new movement-segment event streams.
- Built replay and rebuild tooling for segment correction.
- Optimised throughput and reliability for high-volume event processing.
Condition Monitoring & Wagon Analytics
- APIs and backend services for wagon condition monitoring.
- Brake-wear prediction processing and wagon analytics functionality.
- PostgreSQL views and optimised query models for operational dashboards.
Operational Reliability - First Responder
- Investigated production incidents and distributed-system failures; DLQ analysis, replay and operational recovery.
- Tuned database performance and AWS infrastructure under production load.
- Improved observability, monitoring and operational tooling.
- Supported rollout strategies, monitoring and post-deployment stabilisation.
Nune I.
Last position:
Fractional CTO at OpsWorker
OpsWorker turns Kubernetes alerts into root-cause analyses, on top of the monitoring a team already runs. I lead the technical side: the agent architecture, the AWS infrastructure it runs on (fully inside EU regions), and the engineering decisions behind it, read-only in the cluster by default, human in the loop for judgment. The stack underneath: Amazon Bedrock and Bedrock AgentCore, agents built with the Strands Agents SDK, the Claude and OpenAI APIs, and the Kubernetes API.
Jan K.
Last position:
Data Expert at Manufacturing
Daniel B.
Last position:
Senior Cloud Consultant and Developer at SDIA/Leitmotiv
- Consulting an NGO in the field of data center sustainability in publicly funded projects (BMUKN with NADIKI and Umweltbundesamt with SIEC)
- Development of Python APIs and web applications, deployment on AWS/ECS with Terraform
- Collecting power consumption metrics for servers, CPUs, GPUs running AI workloads
- Technologies used: AWS, EC2, ECS, Fargate, CloudMap, VPC, Route53, Lambda, EventBridge, CodeBuild/CodePipeline/CodeDeploy, Terraform, Docker, Linux, Bash scripting, Python, Flask, SQLAlchemy, SQL, MariaDB, InfluxDB, Telegraf, Prometheus, Zabbix, Kubernetes, Letsencrypt, certificate management
Yannick T.
Last position:
Cloud Architect at Anonymous
- Implementation of Infrastructure as Code (IaC) with Terraform to ensure a scalable, repeatable, and secure Azure infrastructure
- Implementation and optimization of CI/CD pipelines with Azure DevOps
- Management of container and server environments and AKS
Roxana G.
Last position:
Freelance Senior Frontend Developer at RHI Magnesita
- Designed and developed a high-performance internal resource management platform using React and TypeScript, optimizing dynamic data rendering and state management.
- Built a React Native application to support mobile access to internal tools, enabling on-the-go project tracking for field teams.
- Developed custom 2D canvas-based visualizations using Pixi.js to simulate material flows and refractory layer behaviors.
- Integrated Pixi.js with React components for interactive diagrams and real-time UI updates.
- Developed interactive 3D visualizations using React.js for displaying refractory product layouts and simulations, supporting engineering and sales teams with dynamic product previews.
- Integrated Three.js within the React ecosystem to allow manipulation of 3D models in real-time via browser, enhancing user engagement and field configurability.
- Integrated a headless CMS to enable dynamic content updates by non-technical users, reducing content deployment time by 40%.
- Led AWS CloudFront optimization initiatives, improving portal load speeds by 30% globally.
- Actively collaborated with cross-functional Agile teams and product owners to deliver prioritized features with a fast feedback loop.
- Key Technologies: React.js, React Native, Three.js, TypeScript, Contentful CMS, AWS S3/Lambda/CloudFront, Cypress, Agile Scrum
Cesar S.
Last position:
Lead Cloud Engineer at Charge-V GmbH
- Responsible for setting up and configure AWS Organizations and Control Tower on company's master organizational account
- Administer and maintain various AWS services, including EC2, S3, RDS, Lambda, VPC, IAM, etc.
- Monitor system performance, availability, and capacity planning to ensure scalability and reliability
- Implement and maintain infrastructure as code (IaC) using tools like CloudFormation or Terraform
- Work closely with development and operations teams to automate deployment processes using CI/CD pipelines (e.g., Jenkins, GitLab CI/CD)
- Develop and maintain scripts for automating routine tasks and infrastructure provisioning
- Implement automation for monitoring, logging, and alerting to ensure timely incident response
- Implement and enforce security company guidelines and best practices for AWS environments
- Configure and manage AWS security services such as AWS Identity and Access Management (IAM), AWS WAF, AWS Shield, etc.
- Collaborate with the Security Team to improve and update security policies and posture
- Collaborate with development teams to provide agile deployments and optimize application performance and reliability on AWS
- Provide technical support and guidance to internal teams on AWS-related issues and best practices
- Participate in cross-functional projects to enhance overall infrastructure and operational efficiency
Banjika N.
Last position:
Freelance | AWS Authorized Instructor at Go Courses
- Delivered AWS-authorized content through AAI program
- Facilitated group and 1-on-1 mentorship sessions
- Coached non-technical learners into cloud career paths
- Created learning materials aligned with AWS Skill Builder and AWS Academy labs
Tan P.
Last position:
DevOps Engineer in the DevOps Team at Rise-World
- Implementation of specified DevOps solutions to automate infrastructure (Terraform, Bicep, CloudFormation, Ansible) on-premises datacenter (Ovirt, Proxmox, Ceph Cluster, MinIO) and private cloud.
- Administration, configuration and implementation of CI/CD DevOps pipelines (GitLab, GitFlow) to support development process (Artifactory, Prometheus, Istio, service mesh, Helm Chart, OpenShift (Red Hat Enterprise) / Kubernetes cluster), Red Hat Satellite.
- Administration, setup, monitoring and patching of Linux infrastructure based on Red Hat Enterprise for Dev, Test and QA.
- Use of Scrum and Kanban methods.
- Administration, configuration and implementation of security standards for deploying on Dev, Test, QA and Prod stages of the new ePA applications.
- Development of new plugins and add-ons needed on current infrastructure.
- Database support.
- Data analytics support (Python, Spark, Pandas, Power BI, Splunk Enterprise).
- Implementation of best practices for DevSecOps and BizDevOps using GitOps (ArgoCD), Streamlit framework, Semaphore Ansible UI.
- Configuration and testing of iperf, uperf, sysbench using benchmark-operator for external source data and IoT/MDM devices, creating reports via ELK / OpenSearch.
- Building a new Databricks platform to collect and analyze big data from different sources and IoT devices into Hadoop framework (Python, Pandas, PySpark, Power BI, Apache Airflow).
- Building backend data aggregation and processing to automate configuration deployment between different OpenShift clusters and big data framework (Python, Pandas, PySpark, Apache Spark, PostgreSQL, Django 2, Ansible Automation, Jira JSM).
- Building a new ML pipeline platform using Kubeflow, TensorFlow, KServe.
- Data extraction, transformation and loading from different data sources including structured and unstructured data to analytic DWH / big data cluster using Python, Pandas, Polars, Power BI, Django backend and PostgreSQL.
- Setup of new DevOps Test and QA HashiCorp Vault cluster for PKI and IAM.
- Configuration and testing of automated patching based on CVSS score, SIEM-integrated CVEs.
- Use of Nexpose and InsightVM to scan vulnerability events in network, host, container and application.
- Design and implementation of secure and scalable AWS architectures including VPC, EC2, S3, RDS and Route53 and similar setups on Azure and GCP.
- Automated system provisioning and deployment using CloudFormation templates.
- Configuration of IAM roles, policies and permissions to ensure secure access control.
- Patch management, backup automation and disaster recovery setup on AWS infrastructure.
- Monitoring and optimization of system performance using AWS CloudWatch and AWS Trusted Advisor.
- Support of VMware services (vSphere, Aria, Horizon) and the virtual desktop environment.
- Development and maintenance of CI/CD pipelines using Jenkins, GitLab CI/CD and AWS CodePipeline with interface to Nutanix.
- Configuration of AWS CloudWatch to monitor application performance and system events.
- Planning and execution of migration of on-premises applications to AWS cloud platforms.
- Deployment of containerized applications using Docker and Kubernetes in AWS environments.
- Deployment of internal software packages between availability zones using AWS CodeDeploy.
- Building and deploying ML models using Scikit-learn, XGBoost and Spark MLlib including hyperparameter tuning, model evaluation and production deployment.
Alexey G.
Last position:
Cloud Architect & DevOps, Head of Architecture at ProSiebenSat.1 Digital GmbH / Seven.One Entertainment Group GmbH
- Co-authored enterprise cloud strategy including security and governance frameworks for 5 subsidiaries, and implemented part of the governance automation.
- Performed regular cloud cost optimization reviews across 10 teams resulting in ~20% cost reduction.
- Led the technology selection for the migration of in-house CIAM for 25M+ accounts to a SaaS solution, and worked with the product team through the migration.
- Supervised the technology selection and designed the architecture and delivery pipelines for the multi-tenant digital news and sports publishing platform, enabling ~250 editors within ~6 months of development start.
- Led the implementation of a multi-brand design system from idea and technical concept to implementation and rollout, enabling rapid UI prototyping for new products in a matter of hours.
- Managed a team of 4 architects and accelerated the professional growth of team members.
- Technologies: AWS cloud, Microservices, Docker, Python, Kafka, JavaScript, TypeScript, React.js, Node.js, GraphQL, REST, Gitlab CI, Visual Studio Code, git.
Vitalij B.
Last position:
Cloud Engineer at amplimind (Jointventure by Audi & Lufthansa Industry)
- Designed a hybrid AWS platform combining 10+ ECS Fargate microservices (Spring Boot) and Angular/React frontends with a serverless ETL pipeline based on Lambda, S3, SQS/SNS and DynamoDB
- Built a serverless notification service (Lambda + SNS/SQS) enabling event-driven workflows across microservices
- Automated all infrastructure using AWS CDK v2 with reusable constructs that significantly reduced provisioning time
- Implemented blue/green & canary deployments via GitHub Actions and CodePipeline for safe, repeatable releases
- Strengthened observability via CloudWatch and OpenSearch dashboards, alerts and standard runtime checks
- Developed backend services in Java (Spring Boot) and TypeScript with clean REST APIs for modern SPAs
Discover over 15,000 top freelancers
Statistics of experts using AWS CodePipeline
Aggregated from the professional profiles of matched freelancers.
Experience
18 years

Position duration
2 years

Positions per freelancer
12

Top business areas
Information Technology, Product Development, Operations

Top industries
Information Technology, Automotive, Transportation

Certification focus areas
Information Technology, Business Intelligence, Operations
Bachelor's degree or higher
100%
Master's degree or higher
50%

Certifications per freelancer
5

Most common languages
German, English, Russian

Speak two or more languages
100%
Based on our profile pool as of 19 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Germany are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Average rates of experts in Germany using AWS CodePipeline
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
AWS CodePipeline experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (94%)
- Automotive (65%)
- Transportation (41%)
- Retail (41%)
- Aerospace and Defense (35%)
- Banking and Finance (29%)
- Manufacturing (29%)
- Media and Entertainment (29%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What CodePipeline Does
AWS CodePipeline is a managed continuous integration and continuous delivery service for automating software release workflows. It moves changes through source, build, test and deployment stages, helping teams deliver applications and infrastructure consistently. Many teams also search for it simply as CodePipeline.
Core AWS Connections
CodePipeline connects closely with AWS CodeCommit, GitHub, Bitbucket, Amazon S3, AWS CodeBuild, AWS CodeDeploy, Amazon ECS, Amazon EKS and AWS CloudFormation. Strong specialists understand how these services exchange artifacts, credentials, approvals and deployment signals. They also work with IAM, Amazon CloudWatch, AWS CloudTrail and Amazon Elastic Container Registry.
Typical Delivery Work
- Create pipelines for branches, repositories and release environments
- Build, test and package applications with AWS CodeBuild
- Deploy to EC2, ECS, EKS, Lambda, S3 and CloudFormation targets
- Add manual approvals, rollback paths and release gates
- Configure encrypted artifacts, notifications and pipeline monitoring
When Specialists Help
Companies bring in freelance expertise when a pipeline is unreliable, releases require too much manual work or several AWS accounts must follow the same delivery pattern. Professionals can modernize a legacy process, establish reusable pipeline templates or support a migration from Jenkins, GitLab CI/CD or another automation system. In Germany, remote collaboration is common, while regulated or complex environments may still require on-site workshops.
Skills That Matter
Effective CodePipeline specialists combine release automation with practical AWS knowledge. They should be comfortable with IAM policies, VPC networking, containers, serverless deployments, infrastructure as code and secure secret handling. Experience with AWS CDK, Terraform, CloudFormation, YAML configuration, Git workflows and observability makes their solutions easier to operate.
Judging the Result
A strong professional makes every stage clear, repeatable and easy to troubleshoot. Ask how they handle failed actions, artifact versioning, approvals, parallel environments, secrets and rollback. Review a pipeline design or delivery runbook, then check whether it supports least-privilege access, useful logs and safe changes rather than merely completing a successful deployment.
Frequently asked questions
Key details about AWS CodePipeline, drawn from the questions we get asked most.
AWS CodePipeline automates the flow from a source repository through build, test, approval and deployment stages. It is commonly used for applications, containers, serverless workloads and infrastructure managed through CloudFormation or other AWS services.
AWS CodePipeline is a managed AWS service with strong integration across CodeBuild, CodeDeploy, ECS, EKS, Lambda and CloudFormation. Jenkins and GitLab CI/CD can offer broader customization or a more centralized experience, but they may require more ownership of runners, plugins, upgrades and security.
A capable AWS CodePipeline specialist should also understand Git, IAM, AWS CodeBuild, containers, infrastructure as code and deployment targets such as ECS or Lambda. Knowledge of AWS CDK, Terraform, CloudFormation, CloudWatch and secure secrets management is especially useful.
The required depth depends on the delivery landscape rather than a fixed duration. A straightforward pipeline may need focused configuration, while multi-account releases, compliance controls, complex branching and blue-green deployment require a professional who has handled comparable AWS environments.
AWS CodePipeline is well suited to remote collaboration because configuration, logs, approvals and deployment history are available through shared AWS environments. Teams in Germany should agree on access windows, documentation, communication language and any on-site workshops needed for security or release-process decisions.
A well-designed AWS CodePipeline setup uses least-privilege IAM roles, encrypted artifacts, controlled approvals and isolated environments. Specialists should also address secret storage, audit trails, branch permissions, dependency checks and clear rollback procedures.
Look for readable stages, reliable failure handling, useful notifications and repeatable infrastructure. A strong AWS CodePipeline implementation documents its assumptions, limits permissions, separates environments and makes it easy to identify which change caused a failed release.
Yes. AWS CodePipeline can replace or complement Jenkins when the target process fits AWS-managed source, build and deployment services. A specialist should first map existing triggers, plugins, credentials, test steps, artifacts and rollback behavior before proposing a migration.
The average hourly rate of freelancers in Germany who have used AWS CodePipeline in their recent projects is 97 €, which corresponds to a daily rate of about 777 € based on an 8-hour working day.
Of the freelancers in Germany who have used AWS CodePipeline in their recent projects, 100% hold at least a Bachelor's degree and 50% hold at least a Master's degree.
On average, freelancers in Germany who have used AWS CodePipeline in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 2 years.
The most common languages among freelancers in Germany who have used AWS CodePipeline in their recent projects are German (100%), English (100%), and Russian (29%).
The most common industries among freelancers in Germany who have used AWS CodePipeline in their recent projects are Information Technology (94%), Automotive (65%), and Transportation (41%).
The most common business areas among freelancers in Germany who have used AWS CodePipeline in their recent projects are Information Technology (100%), Product Development (76%), and Operations (65%).
Main locations of FRATCH Experts, who have recently used AWS CodePipeline
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
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